Medium Levels Research Articles

Assessing Students’ Critical Thinking in Dialogue

Critical thinking has been widely considered an important skill in the 21st century. In view of the value attached to critical thinking, various quantitative instruments have been developed to assess critical thinking, which only provide a product of critical thinking and cannot reveal the critical thinking process of test takers. Hence, this paper proposes a coding scheme facilitating a qualitative analysis of critical thinking exhibited in interaction. The coding scheme consists of five categories of critical thinking skills, i.e., analysis, comparison, evaluation, inference, and synthesis, each of which is coded at low, medium, and high levels. The use of this coding scheme is then illustrated by applying it to authentic classroom dialogue. This coding scheme is hopefully conducive to the assessment of critical thinking in educational settings.

Modified throughput ninhydrin method for the qualitative assessment of dietary protein absorption in pig plasma.

Protein maldigestion and malabsorption lead to malnutrition and are a feature of exocrine pancreatic insufficiency (EPI). Although it is the current standard, measurement of nitrogen in stool to assess protease activity is indirect. Up to 80% of hydrolysed proteins appear in blood in the form of peptides, so we developed a method to measure peptide-derived amino acids in plasma as a relevant measure of proteolysis, verified its accuracy, precision, and linearity, and validated it in a porcine model. We modified a ninhydrin method. Large proteins were eliminated from plasma with 10 kDa-cut-off centrifugal filters. Free and total amino acids were measured in permeate before and after its hydrolysis. Peptide-derived amino acids were quantified by subtracting free amino acids from total amino acids. We verified the method in vitro and by comparing results in healthy and EPI pigs. The accuracy of the analysis was close to 100%, with excellent precision (mean relative standard deviation for low, medium, and high amino acid levels = 0.88%) and with stringent linearity (r2 = 0.986, %RE = 5.23). The high-throughput ninhydrin method detected levels of peptide-derived amino acids in vivo with maximal changes seen approximately 2 hours postprandially in young pigs. The AUC and Cmax were significantly higher in healthy compared to EPI pigs (P = .0026 and P = .0037, respectively). The high-throughput ninhydrin method is a sensitive, reliable, and practical method for the estimation of dietary peptide-derived amino acids. This assay endpoint could serve as a direct biomarker of protein digestion and absorption.

Improvement of Saline–Alkali Soil and Straw Degradation Efficiency in Cold and Arid Areas Using Klebsiella sp. and Pseudomonas sp.

Corn straw is an important renewable resource, which could improve the quality of saline–alkali cultivated land. However, the slow decomposition of crop residues in cold, arid, and saline–alkali soils can lead to serious resource waste and ecological crises. The use of beneficial microorganisms with degradation functions could solve these problems. In this study, three types of saline–alkali soil with low, medium, and high salinity levels were used in the straw-returning experiment. The experiment was conducted with four treatments: GF2 (Klebsiella sp.), GF7 (Pseudomonas sp.), GF2+GF7, and CK (control without bacteria). Microbial characteristics, straw degradation efficiency, element release rate, and soil factors were compared, and random forest linear regression and partial least squares path modeling analysis methods were utilized. The results indicated that the degradation of bacterial metabolites, the efficiency of corn stover degradation, the efficiency of component degradation, and the release rates of elements (C, N, P, and K) initially increased and then decreased with the increase in salinity. At the maximum value of moderately saline–alkali soil, the effect of GF2+GF7 treatment was significantly better than that of other treatments (p < 0.05). Given the interactive effects of saline–alkali soil and microbial factors, the application of exogenous degrading bacteria could significantly increase soil enzyme activity and soil available nutrients, as well as regulate the salt–alkali ion balance in soil. The cation exchange capacity (9.13%, p < 0.01) was the primary driving force for the degradation rate of straw in saline–alkali soil with different degrees of salinization under the influence of exogenous degrading bacteria. Straw decomposition directly affected the soil chemical properties and indirectly affected soil enzyme activity. The results of this study would provide new strategies and insights into the utilization of microbial resources to promote straw degradation.

Studying the X-ray absorption characteristics of Centaurus X-3 using nearly 14 years of MAXI/GSC data

Centaurus X-3 is a persistent high-mass X-ray binary with the long-term light curve from the source exhibiting orbit-to-orbit intensity variations with no apparent superorbital periodicity. We used sim 13.5 years of MAXI /GSC data to study the long-term behaviour of X-ray absorption caused by the stellar wind from the companion star and any absorbing structures present in the binary. We used orbital-phase-resolved spectroscopy to study the variation in the photoelectric absorption along the line of sight of the source for both the intensity-averaged data and intensity-resolved data after dividing all the data binned with orbital period into three intensity levels. We find an asymmetric variation in the photoelectric absorption along the line of sight across an orbit of the source. The orbital-phase-resolved spectra show a clear increase in photoelectric absorption after $ orb 0.5, which deviates from a spherically symmetric stellar wind model. The flux of Cen X-3 shows significant variation between consecutive orbits. An intensity-resolved spectral analysis of the source was performed, followed by an intensity-resolved and orbital-phase-resolved spectral analysis, which showed that at the medium and high intensity levels, the orbital-phase-resolved photoelectric absorption is slightly asymmetric with respect to mid-phase ($ orb =$ 0.5). The asymmetry is very pronounced at the lowest intensity level and cannot be explained by a spherically symmetric wind from the companion star. The differences in the orbital phase-dependence of absorption for different intensity levels suggest that the presence of an accretion wake, photoionization wake, or tidal stream is more prominent at a lower intensity level for Centaurus X-3 than at a higher intensity level.

Effects of combined application of phosphorus and zinc on growth and physiological characteristics of apple rootstock M9-T337 seedlings (Malus domestica Borkh.)

BackgroundBalancing nutrient application is crucial for plant growth. However, excessive fertilizer use, especially imbalanced applications of macronutrients such as phosphate (P), can hinder plant uptake of micronutrients. Balanced P and zinc (Zn) are vital for apple yield and quality, and apple trees are highly sensitive to deficiencies in these nutrients. Therefore, this study was conducted in May 2022, employed a sand culture experiment to investigate the effects of varying P and Zn levels on the growth phenotype, photosynthetic capacity, antioxidant enzyme activity, sugar composition, endogenous hormone levels, and nutrient absorption and utilization of M9-T337 seedlings. Three levels of P (low, medium, high) and three levels of Zn (low, medium, high) were combined to create a total of nine distinct treatment.ResultsThe results indicate that combined P and Zn fertilization at various levels exerts either synergistic or antagonistic effects on the growth, nutrient absorption, and utilization of M9-T337 seedlings. Compared to low and medium levels of P, a combination of high P (4 mmol·L−1) and an adequate amount of Zn significantly enhanced plant growth, root system development, and the microstructure of leaves. Notably, seedlings treated with high P and low Zn (HPLZn) reached a height 1.54 times that of the medium P and medium Zn (MPMZn, control). Physiological indicators under HP conditions revealed significant increases in antioxidant enzyme activity, leaf water retention, photosynthetic pigment concentration, osmotic adjustment substances, and the contents of glucose, sucrose, fructose, endogenous hormones, as well as P and Zn accumulation in the leaves, compared to the control. However, an increase in Zn application led to a declining trend in these parameters. Specifically, the HPLZn treatment exhibited substantial increases in Net photosynthetic rate (Pn), Total chlorophyll (Chl a + b), glucose, fructose, sucrose, and Auxin(IAA), with increments of 7.12%, 27.32%, 11.40%, 23.20%, 16.67%, and 55.11%, respectively, compared to the control.ConclusionBased on the comprehensive ranking from principal component analysis, the combination of HP ( 4 mmol·L−1) and LZn (0.5 µmol·L−1) was found to be the most effective in enhancing the antioxidant capacity, sugar accumulation, osmotic regulation ability, photosynthetic capacity, endogenous hormone levels, as well as P and Zn nutrient absorption and utilization in M9-T337 seedlings.

Entropy Engineering of 2D Materials.

Entropy, a measure of disorder or uncertainty in the thermodynamics system, has been widely used to confer desirable functions to alloys and ceramics. The incorporation of three or more principal elements into a single sublattice increases the entropy to medium and high levels, imparting these materials a mélange of advanced mechanical and catalytic properties. In particular, when scaling down the dimensionality of crystals from bulk to the 2D space, the interplay between entropy stabilization and quantum confinement offers enticing opportunities for exploring new fundamental science and applications, since the structural ordering, phase stability, and local electronic states of these distorted 2D materials get significantly reshaped. During the last few years, the large family of high-entropy 2D materials is rapidly expanding to host MXenes, hydrotalcites, chalcogenides, metal-organic frameworks (MOFs), and many other uncharted members. Here, the recent advances in this dynamic field are reviewed, elucidating the influence of entropy on the fundamental properties and underlying elementary mechanisms of 2D materials. In particular, their structure-property relationships resulting from theoretical predictions and experimental findings are discussed. Furthermore, an outlook on the key challenges and opportunities of such an emerging field of 2D materials is also provided.

Nurses' strategies for coping with stress in the face of the influx of war refugees from Ukraine to Poland.

Russian military's incursion into Ukraine sparked the largest refugee crisis in Europe since World War II. As Ukraine's neighboring country, Poland became the primary destination for these refugees. Ukrainians staying in Poland under the EU's Temporary Protection Directive receive humanitarian support similarly to asylum seekers, but the legal pathways, length of stay and integration processes differ significantly as the Directive provides for more immediate, collective protection without the complexity of individual asylum applications. The influx of war refugees generates extremely complex situations that health personnel, especially nurses, must face on a daily basis. Identify whether and to what extent the emergence of a large number of patients with war-related experiences constituted a source of stress for nurses, and how Polish nurses coped with this issue. A cross-sectional study was conducted in December 2022 in Białystok, Poland. It included 473 certified nurses working in hospitals affiliated with the District Chamber of Nurses in Białystok. Perceived Stress Scale (PSS-10) questionnaire and Mini-COPE inventory (Polish version of Carver'a BriefCOPE inventory were used in the study. The average stress level among nurses was moderate, with nearly equal proportions of nurses experiencing low, medium, and high stress levels. Nurses who had contact with refugees in the last six months and/or helped them, did not present an increased level of stress - on the contrary, this level was lower. Nurses who helped refugees at work more often used a planning strategy in stressful situations, and less frequently reacted to stress using humour, religion, denial or venting. The greater workload and more frequent contacts between Polish nurses and Ukrainian war refugees were a factor increasing work fatigue, but, paradoxically, at the same time reducing the level of stress in a situation giving the feeling of a duty well fulfilled. Empowering nurses through greater autonomy and fostering supportive work environments, especially in crisis situations like the care of war refugees has a positive impact on coping with stress.

Correlation between teacher competence and the self-efficacy of secondary school teachers

The purpose of this study was to compare the different levels of teacher competence and self-efficacy among secondary school teachers. A comparative survey method for descriptive research was used. A total of 147 secondary school teachers were selected through a random sampling method. Analysis of variance was used for data analysis. The key finding of this study is that among male and female teachers with high, moderate, and low competency levels, there are no significant differences in self-efficacy. Government teachers show no significant differences in self-efficacy with respect to their competence levels, but private teachers show an apparent pattern. Private teachers differ only in terms of high and low levels of self-efficacy; neither high nor medium self-efficacy levels differ from one another.

Development and Evaluation of an Out-of-Control Scale Measuring Global Contextual Stressors Across 20 Countries and Regions

Abstract: Stressful contexts like the COVID-19 pandemic precipitated remarkable socio-economic changes, exacerbating universal uncertainty and a pervasive loss of control. Improving mental health outcomes on the operational definition and measurement of related concepts. This study analyzed cross-sectional data from 20 countries and regions, collected between January 25 and November 10, 2021. Psychometric evaluation occurred in two stages: initially, item review and factor analysis with a 2,749 adult sample from Mainland of China and Hong Kong SAR; subsequently, confirmation of factor structure, measurement invariance testing, and advanced analyses with a 4,000 adult sample from 20 countries and regions. A six-item, single-factor structure was verified, confirming satisfactory factor loading, fit indices and consistency. Measurement invariance across geographies and groupings was also confirmed. Three Out-of-Control profiles representing low, medium, and high stress levels, were identified, with age, depression/anxiety symptoms, education, socio-economic status, and exposure to COVID-19-affected acquaintances significantly influencing affiliation. The item “I think I cannot control things that I previously could” was the most critical node. This newly validated scale represents a substantial advancement in measuring stress within the context of global health crises, thus enhancing comprehension of psychological responses. Continual evaluation of the scale’s effectiveness and accuracy is crucial.

Does the development of strategic readiness represent a response to the relationship of strategic competencies and the healthcare information system? Evidence from private hospitals in Jordan

This study introduces a model designed to improve the strategic readiness of private hospitals in Amman by incorporating strategic competencies as an independent variable and using a healthcare information system as a mediator. Targeting private hospitals with over 140 beds, the research included a population of 3263 employees across various managerial levels. Data collection methods involved interviews and electronic questionnaires, resulting in a sample size of 344. Statistical analyses comprised exploratory and confirmatory factor analysis, structural equation modeling, and hypothesis testing with SMART PLS 3.3.3 software. The results indicated medium levels of both strategic competencies and healthcare information systems, while strategic readiness was found to be low. Nevertheless, the proposed model showed a direct positive effect of strategic competencies on strategic readiness, with the healthcare information system acting as a significant partial mediator. Evaluation metrics included the arithmetic mean, standard deviation, and path analysis. This model surpasses traditional methods by effectively linking strategic competencies and information systems to enhance strategic readiness, providing a strong framework for improving hospital responses to crises and dynamic changes. The study suggests focusing on enhancing and developing strategic competencies and integrating a comprehensive healthcare information system to optimize hospital operations and increase readiness.

Reinforcement Learning to Optimize Ventilator Settings for Patients on Invasive Mechanical Ventilation: Retrospective Study.

One of the significant changes in intensive care medicine over the past 2 decades is the acknowledgment that improper mechanical ventilation settings substantially contribute to pulmonary injury in critically ill patients. Artificial intelligence (AI) solutions can optimize mechanical ventilation settings in intensive care units (ICUs) and improve patient outcomes. Specifically, machine learning algorithms can be trained on large datasets of patient information and mechanical ventilation settings. These algorithms can then predict patient responses to different ventilation strategies and suggest personalized ventilation settings for individual patients. In this study, we aimed to design and evaluate an AI solution that could tailor an optimal ventilator strategy for each critically ill patient who requires mechanical ventilation. We proposed a reinforcement learning-based AI solution using observational data from multiple ICUs in the United States. The primary outcome was hospital mortality. Secondary outcomes were the proportion of optimal oxygen saturation and the proportion of optimal mean arterial blood pressure. We trained our AI agent to recommend low, medium, and high levels of 3 ventilator settings-positive end-expiratory pressure, fraction of inspired oxygen, and ideal body weight-adjusted tidal volume-according to patients' health conditions. We defined a policy as rules guiding ventilator setting changes given specific clinical scenarios. Off-policy evaluation metrics were applied to evaluate the AI policy. We studied 21,595 and 5105 patients' ICU stays from the e-Intensive Care Unit Collaborative Research (eICU) and Medical Information Mart for Intensive Care IV (MIMIC-IV) databases, respectively. Using the learned AI policy, we estimated the hospital mortality rate (eICU 12.1%, SD 3.1%; MIMIC-IV 29.1%, SD 0.9%), the proportion of optimal oxygen saturation (eICU 58.7%, SD 4.7%; MIMIC-IV 49%, SD 1%), and the proportion of optimal mean arterial blood pressure (eICU 31.1%, SD 4.5%; MIMIC-IV 41.2%, SD 1%). Based on multiple quantitative and qualitative evaluation metrics, our proposed AI solution outperformed observed clinical practice. Our study found that customizing ventilation settings for individual patients led to lower estimated hospital mortality rates compared to actual rates. This highlights the potential effectiveness of using reinforcement learning methodology to develop AI models that analyze complex clinical data for optimizing treatment parameters. Additionally, our findings suggest the integration of this model into a clinical decision support system for refining ventilation settings, supporting the need for prospective validation trials.

Knowledge towards health impacts of climate change among Amhara Sayint community, Northeastern Ethiopia

Purpose This study aims to assess the knowledge of Amhara Sayint district community in Northeastern Ethiopia towards the health impacts of climate change. Design/methodology/approach A community-based cross-sectional study was conducted from 20 July to 5 September 2022, involving 605 randomly selected households in Amhara Sayint district, Northeastern Ethiopia. Data were collected through face-to-face interviews using a pilot-tested and content-validated questionnaire administered via Kobo Collect survey tool. The data were then exported to STATA for management and analysis. A proportional odds approach of ordinal logistic regression model was fitted with a 95% confidence level to identify factors associated with the community’s knowledge towards the health impacts of climate change. Findings Of the total respondents, 3.47% (95% confidence interval [CI]: 2.1, 5.3) and 42.98% (95% CI: 38.9, 47) had inadequate and medium levels of knowledge towards the health impacts of climate change, respectively. Proportional odds model analysis result indicated that gender (female) (adjusted odds ratio [AOR] = 1.49; 95% CI: 1.053, 2.13), wealth status (poorest) (AOR = 1.97; 95% CI: 1.01, 3.83), educational status (unable to read and write) (AOR = 4.13; 95% CI: 1.25, 13.68) and participation status in environmental protection activities (not) (AOR = 1.78; 95% CI: 1.17, 2.71) were factors that significantly associated with inadequate and medium levels of knowledge towards the health impacts of climate change. Research limitations/implications The result of this research is not supported by qualitative methods. Practical implications Residents of the study area know the climate is changing; however, they lack adequate knowledge towards the health impacts of climate change. Social implications Significant number of people have inadequate level of knowledge about health impacts of climate change so relevant health education is needed. Originality/value This research is original in its focus on assessing public knowledge about the health impacts of climate change in the Amhara Sayint district, northeastern Ethiopia, a perspective often overlooked in existing studies. Its findings are crucial for guiding future research and developing targeted public health strategies and educational initiatives.

Draw-a-Person Test

The Draw-a-Person test is a screening instrument used to assess children’s non-verbal intelligence. In the assessment of children, brief criteria of DAP’s could be promising to identify possible learning difficulties. Therefore, our aim was to propose a reduced number of criteria to evaluate DAP. To do so, 1403 children aged from 6 to 10 years (M = 8.16; SD = 1.40) participated. Through the mirt package in the R Studio program, we proposed a 2-parameter logistic model, extracting 12 indicators that were able to predict 83% of non-verbal intelligence. In this correction proposal, we selected indicators that maintained easy, medium, and difficult levels, which allowed children’s performance to differentiate according to age. The results were positive, indicating that the proposal is promising for use in research, clinical practice, psychoeducation, and educational psychological assessments.

A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor

Western Monarch butterflies (Danaus plexippus) migrate from inland breeding ranges to coastal overwintering grounds in California. Given that migratory individuals may make multi-scale habitat selection decisions, we considered a multi-scale species distribution model (SDM) using range-wide climatic and local landscape-level predictors of migratory and overwintering habitat and community-science presence data. The range-wide model output was included as a predictor in the local-scale model, generating multi-scale habitat suitability. The top range-wide predictor was the minimum temperature in December, contributing 83.7% to the model, and was positively associated with presence. At the local scale, the strongest predictors of presence were the range-wide output and percent coverage of low and medium levels of development, contributing > 95%, with 61–63% from the range-wide output, with local-scale suitability coinciding with the California coastal zones. Development’s positive association with overwintering monarch presence was counterintuitive. It is likely that our local-scale model is overfit to these development zones, but it is unclear whether this overfitting resulted from modeler choices, monarchs overwintering close to human development, biased detection near human development, or a combination of these factors. Therefore, alternative approaches to collecting local-scale attribute data are suggested while recognizing the primacy of climate in restricting overwinter sites.

Cancer-related Fear and Worry in Patients with Low-Risk Thyroid Cancer: A Longitudinal Cohort Study.

Little is known about how patients' emotions impact the choice between hemi- and total thyroidectomy (TT) for low-risk thyroid cancer (LR-TC) and how these emotions change after treatment. To investigate thyroid cancer-specific fear and worry both before and after treatment of LR-TC with hemi- or TT. This prospective cohort study enrolled adults with confirmed or likely LR-TC at 15 institutions. Participants completed measures of thyroid cancer-related fear and worry at the time of their treatment decision and 9-months later. Participants were categorized as having low, medium, or high levels of fear and worry in accordance with the literature. Those choosing hemi-thyroidectomy were compared to those choosing TT. Of 177eligible patients, 125 (70.6%) enrolled and 114 completed both surveys (91.2% retention). Overall, 41 (36.0%) participants chose hemi-thyroidectomy and 73 (64.0%) chose TT. Across all participants, thyroid cancer-related fear and worry both decreased significantly after surgery (fear 25.8±6.4 to 23.1±7.4; worry 8.2±2.4 to 5.4±2.1, p<0.001). The proportion of participants with high fear decreased from 64.9% to 50.9%, while the proportion with high worry decreased from 75.4% to 41.2% (p<0.001 for both). At both time points, no differences existed between those choosing hemi- and TT in levels of worry or fear. Patients with LR-TC report lower levels of fear and worry 9-months after surgery regardless of the extent of surgery, suggesting that both surgeries provide an emotional benefit to some patients. Thyroid cancer-related fear and worry do not appear to influence patients' decisions to undergo hemi- or TT.

The power of play: gamification in virtual workplace training

ABSTRACT Organizations face growing pressure to upskill their employees and provide effective and engaging training, leading to significant investments in virtual workplace training (VWT). However, the effectiveness of VWT, particularly when incorporating game elements, remains unclear. To address this, this study examined the impact of gamification intensity on perceived autonomy and its effect on training outcomes. Additionally, it explored whether self-efficacy played a moderating role in these relationships. Using a between-subjects design, we manipulated gamification intensity (low, medium and high levels) and asked 355 employees to complete a VWT and a retention test. In contrast to our expectations, gamification intensity negatively affected perceived autonomy. Furthermore, perceived autonomy had a positive impact only on affective but not on performance-related training outcomes. Also, we found no evidence of the mediating role of perceived autonomy or the moderating role of self-efficacy in these relationships. Regarding the retention test, gamification intensity negatively affected perceived autonomy and both affective and performance-related training outcomes. Our findings challenge the belief that gamification intensity enhances satisfaction and training success and underscore the importance of autonomy in VWT. We discuss how our findings can guide researchers and practitioners to promote sustainable training success in organizations.

Revealing the Response of Cucumber Soil Microbial Community Composition and Function to Nitrogen Addition in Northern Chinese Greenhouses

At present, the soil of Chinese greenhouses is experiencing severe nitrogen input in the form of fertilizer, which will cause damage to the soil environment and restrict crop growth in the long run. The response of potential functions of microorganisms as drivers of nutrient cycling and material transformation to nitrogen enrichment has rarely been reported in northern vegetable planting systems. Therefore, we set up four cucumber pot experiments with different nitrogen addition rates (0, 258, 516, and 1032 kg N ha−1 yr−1) in the greenhouse. Bacterial and fungal communities were detected by 16S and ITS rRNA gene sequencing, and bacterial and fungal functional groups were predicted using the FAPROTAX and FUNGuild databases. The findings showed that nitrogen addition induced soil acidification (a decrease of 0.25–1.63 units) significantly reduced microbial diversity and changed the community composition of bacteria and fungi. The relative abundance of bacterial functional groups associated with the nitrogen cycle increased significantly when medium and high levels of nitrogen were added. Conversely, the bacterial functional groups involved in the carbon cycle exhibited the opposite pattern. In this study, NO3− and soil pH were the main factors affecting the soil microbial community and its functional groups. Our results highlight that hydrocarbon degradation and saprophytic fungi may play key roles in yield formation during cucumber cultivation in northern solar greenhouses. In general, adopting a fertilization strategy that ensures low-medium nitrogen availability can contribute to the sustainable progress of facility agriculture.

Microwave scattering properties of ice crystal particles during the melting process

Ice crystal particles play an important role in the study of cloud resolution, climate models, and radiative forcing. During the melting process, significant changes occur in the microphysical properties of ice crystal particles, such as the ice phase state, morphology, and mixing state. This process further affects the scattering and radiation characteristics properties of ice crystal particles. In this study, we constructed a non-spherical and inhomogeneous particle model based on the melting process of ice crystal particles. The scattering properties of melting ice crystal particles under four selected microwave frequency bands (92 GHz, 220 GHz, 280 GHz, and 340 GHz) are investigated by using discrete dipole approximation (DDA) method. The influence of ice crystal content (ICC) and particle aspect ratio on the scattering properties of ice crystal particles under thin coating and medium coating conditions are emphasized. The results show that the melting process significantly affects the scattering properties of melting ice crystal particles in a frequency dependent manner. Additionally, even slight melting of ice crystal particles leads to drastic changes in their scattering properties. Furthermore, we found that the morphology of ice crystal nuclei has a significant impact on their scattering characteristics even at medium levels of melting degree. In summary, this study confirms that it is essential to consider morphology and inhomogeneous characteristics during the melting process for microwave detection of ice crystal particles. This research may have significant implications for studies related to detection and inversion techniques for ice crystal particles.

Docosahexaenoic acid (DHA) is a driving force regulating gene expression in bluefin tuna (Thunnus thynnus) larvae development

This study elucidated the role of DHA-modulated genes in the development and growth of Atlantic bluefin tuna (Thunnus thynnus) larvae ingesting increasing levels of DHA in their rotifer prey. The effect of feeding low, medium, and high rotifer (Brachionus rotundiformis) DHA levels (2.0, 3.6 and 10.9 mg DHA g−1 DW, respectively) was tested on 2–15 days post hatching (dph) bluefin tuna larvae. Larval DHA content markedly (P < 0.05) increased in a DHA dose-dependent manner (1.5, 3.9, 6.1 mg DHA g−1 DW larva, respectively), that was positively correlated with larval prey consumption and growth (P < 0.05). Gene ontology enrichment analyses of differentially expressed genes (DEGs) demonstrated dietary DHA significantly (P < 0.05) affected different genes and biological processes at different developmental ages. The number of DHA up-regulated DEGs was highest in 10 dph larvae (491), compared to 5 (12) and 15 dph fish (34), and were mainly involved in neural and synaptic development in the brain and spinal cord. In contrast, DHA in older 15 dph larvae elicited fewer DEGs but played critical roles over a wider range of developing organs. The emerging picture underscores the importance of DHA-modulated gene expression as a driving force in bluefin tuna larval development and growth.

Using multilayer network analysis to detect the collaborative knowledge construction characteristics among learner groups with low, medium, and high levels of cognitive engagement

Collaborative knowledge construction (CKC) is advanced by group members' cognitive engagement across three levels: individual-level knowledge processing and proposing, the peer-level social interactions and knowledge exchanges between two group members, and the group-level coordination and construction of knowledge across multiple group members. The interconnected and transformative relationship among three levels is an essential factor during the CKC process. Individual viewpoints can trigger peer feedback, which can be further refined by other group members; the group-level consensus can provide foundations for subsequent individual- or peer-level cognitive engagement. The group-level coordination of knowledge advancement involves the processing, synthesis, and reflection of knowledge from multiple members to reach a group consensus. However, previous analytical approaches have faced challenges in modeling distinct types of interconnections across the individual, peer, and group levels during the CKC process. To address this gap, this research employed multilayer network analysis (MNA) to model and quantify the multi-level and interconnected characteristics of CKC in a series of face-to-face, computer-supported CKC activities in China's higher education. First, small groups were categorized into the high, medium, and low levels of cognitive engagement groups. Second, multilayer networks were constructed for each category, where students' use of cognitive strategies were set as nodes, the interconnections between cognitive strategies were set as edges, and three levels (i.e., individual, peer, and group levels) were set as layers. The node-, layer-, and network-level metrics were calculated to quantify the overall characteristics of the networks, the interconnected characteristics within a level and across the three levels. The MNA results revealed that, compared to lower level of cognitive engagement groups, groups with higher cognitive engagement demonstrated (1) more influential moderate and deep cognitive strategies at group and peer levels; (2) interconnections between cognitive strategies with higher diversity, connectivity, and more balanced distribution across three levels, but relatively lower information exchanging efficiency; and (3) communities with more interconnections related to the moderate and deep cognitive strategies at peer and group levels. Based on the empirical findings, this research proposed pedagogical implications for CKC practices and analytical implications for using MNA to improve the understanding of computer-supported collaborative learning mechanisms.